Su Zhang¹, Song Deng^1,*, Qingsheng Liu²

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.072777

Abstract Accurate and reliable power system data are fundamental for critical operations such as grid monitoring, fault diagnosis, and load forecasting, underpinned by increasing intelligentization and digitalization. However, data loss and anomalies frequently compromise data integrity in practical settings, significantly impacting system operational efficiency and security. Most existing data recovery methods require complete datasets for training, leading to substantial data and computational demands and limited generalization. To address these limitations, this study proposes a missing data imputation model based on an improved Generative Adversarial Network (BAC-GAN). Within the BAC-GAN framework, the generator utilizes Bidirectional Long Short-Term… More >

Hanifah Rahmi Fajrin^1,2, Se Dong Min^1,3,*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.072609

Abstract Accurate segmentation of breast cancer in mammogram images plays a critical role in early diagnosis and treatment planning. As research in this domain continues to expand, various segmentation techniques have been proposed across classical image processing, machine learning (ML), deep learning (DL), and hybrid/ensemble models. This study conducts a systematic literature review using the PRISMA methodology, analyzing 57 selected articles to explore how these methods have evolved and been applied. The review highlights the strengths and limitations of each approach, identifies commonly used public datasets, and observes emerging trends in model integration and clinical relevance. More >

Ahmet Ezgi¹, Aytuğ Onan^2,*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.071301

Abstract Knowledge distillation has become a standard technique for compressing large language models into efficient student models, but existing methods often struggle to balance prediction accuracy with explanation quality. Recent approaches such as Distilling Step-by-Step (DSbS) introduce explanation supervision, yet they apply it in a uniform manner that may not fully exploit the different learning dynamics of prediction and explanation. In this work, we propose a task-structured curriculum learning (TSCL) framework that structures training into three sequential phases: (i) prediction-only, to establish stable feature representations; (ii) joint prediction–explanation, to align task outputs with rationale generation; and (iii)… More >

Chee Chin Lim^1,2,*, Hui Wen Tiu¹, Qi Wei Oung^1,3, Chiew Chea Lau⁴, Xiao Jian Tan^2,5

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.070468

Abstract Breast cancer remains one of the leading causes of cancer mortality world-wide, with accurate molecular subtyping is critical for guiding treatment and improving patient outcomes. Traditional molecular subtyping via immuno-histochemistry (IHC) test is invasive, time-consuming, and may not fully represent tumor heterogeneity. This study proposes a non-invasive approach using digital mammography images and deep learning algorithm for classifying breast cancer molecular subtypes. Four pretrained models, including two Convolutional Neural Networks (MobileNet_V3_Large and VGG-16) and two Vision Transformers (ViT_B_16 and ViT_Base_Patch16_Clip_224) were fine-tuned to classify images into HER2-enriched, Luminal, Normal-like, and Triple Negative subtypes. Hyperparameter tuning,… More >

Giada Faraco^*, Andrea Vincenzo De Nunzio, Nicola Ivan Giannoccaro^*, Arcangelo Messina

Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2025.075327

Abstract Damage detection and localization analysis have gained increasing importance over the years, due to the growing number of catastrophic events and the associated risks that small, undetected cracks in structures may evolve into severe failures if not identified in time. In this context, vibration-based methods have been extensively investigated for structural damage detection. Among them, one of the most widely used approaches since its introduction is the curvature method. It has been successfully employed in numerous studies, consistently providing reliable results. However, the use of second-order or higher-order derivatives can be challenging when dealing with… More >

Amy J. Petty^*, Drew A. Emge, Adela R. Cardones

Oncology Research, DOI:10.32604/or.2025.073383

Abstract Skin cancer remains the most commonly diagnosed malignancy worldwide, with basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (cSCC), and melanoma representing the most clinically significant types. While traditional treatments are effective for early-stage disease, advanced or metastatic cases often pose significant therapeutic challenges. Patients with high-risk or recurrent disease face limited options and poor prognoses. The emergence of immunotherapy has dramatically transformed the treatment landscape across multiple cancer types, including cutaneous malignancies. This review highlights recent advancements in immunotherapeutic strategies for BCC, cSCC, and melanoma, underscoring their growing importance in dermatologic oncology. We synthesize More >

Amal F. Gharib¹, Ohud Alsalmi¹, Hayaa M. Alhuthali¹, Afaf Alharthi¹, Saud Ayed Alharthi², Shaimaa A. Alharthi³, Rasha L. Etewa⁴, Wael H. Elsawy^5,*

Oncology Research, DOI:10.32604/or.2025.073051

Abstract Background: Locally advanced laryngeal squamous cell carcinoma (LA-LSCC) presents clinical challenges due to the lack of reliable non-invasive biomarkers. This study aimed to evaluate miR-449a as a diagnostic and prognostic biomarker in LA-LSCC. Methods: miR-449a expression was analyzed in tumor tissues, adjacent normal tissues, and serum from 81 LA-LSCC patients and 50 controls using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). We assessed the diagnostic accuracy by Receiver Operating Characteristic curve (ROC curves), clinicopathological associations, survival outcomes (Kaplan-Meier), and treatment response dynamics. Results: miR-449a was significantly downregulated in LA-LSCC tissues (p < 0.0001) and serum (p <… More >

Myeong Ryeo Kim^1,*, Jae Rim Lee¹, Xiaohan Zhang², Kwang Won Jeong^1,*

Oncology Research, DOI:10.32604/or.2025.072592

Abstract Objectives: Tamoxifen is a key drug that provides endocrine therapy for estrogen receptor (ER) α-positive breast cancer; however, resistance remains a significant clinical challenge. This study aims to investigate the molecular mechanisms of tamoxifen resistance in ERα-positive breast cancer, with particular focus on the role of SET Domain Containing 1A (SETD1A)-driven forkhead box A2 (FOXA2) as a key regulator of this resistance. Methods: FOXA2 expression and its regulation by SETD1A were assessed via (quantitative polymerase chain reaction), western blotting, transcriptome profiling, and chromatin immunoprecipitation analyses. The effects of FOXA2 on cell proliferation, migration, invasion, and cancer… More >

Urszula Częścik^1,2,#, Martyna Gryglas³, Arkadiusz Szterk⁴, Sylwia Flis^3,#,*

Oncology Research, DOI:10.32604/or.2025.067449

Abstract Colorectal cancer (CRC) is the third most common malignancy worldwide and the second leading cause of cancer-related deaths, accounting for approximately 10% of all cancer cases. By 2050, CRC incidence is expected to rise substantially, driven by population aging and greater exposure to risk factors in developing countries. Despite advances in medicine and pharmacy, the effectiveness of available treatments remains limited, underscoring the urgent need for innovative therapeutic strategies. This review summarizes and critically evaluates currently available CRC therapies and explores new emerging directions. Particular attention is given to the role of immunotherapy, targeted therapies,… More >

Siti Norasmah Surip¹, Wan Nor Raihan Wan Jaafar^1,*, Jaka Fajar Fatriansyah², Ing Kong³

Journal of Renewable Materials, DOI:10.32604/jrm.2025.02025-0182

Abstract Most studies on kenaf fibre composites focus on the bast due to its higher fibre yield and strength, while the core is often neglected. In this work, Polylactic Acid (PLA) matrix was reinforced with both kenaf bast and core fibres at a 49:1 wt% ratio. The fibres were chemically treated and cryo-crushed to improve bonding and dispersion. Mechanical testing revealed that treated Kenaf Core Composites (KCC) exhibited comparable flexural and impact properties to Kenaf Bast Composites (KBC), with flexural strengths of 46.19 and 46.52 MPa, respectively, and impact strengths of 5.8 and 4.4 J/m. Meanwhile, More >